White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI

Virtual dissection and comparative connectivity of the superior longitudinal fasciculus in chimpanzees and humans

Many of the behavioral capacities that distinguish humans from other primates rely on fronto-parietal circuits. The superior longitudinal fasciculus (SLF) is the primary white matter tract connecting lateral frontal with lateral parietal regions; it is distinct from the arcuate fasciculus, which interconnects the frontal and temporal lobes. Here we report a direct, quantitative comparison of SLF connectivity using virtual in vivo dissection of the SLF in chimpanzees and humans. SLF I, the superior-most branch of the SLF, showed similar patterns of connectivity between humans and chimpanzees, and was proportionally volumetrically larger in chimpanzees. SLF II, the middle branch, and SLF III, the inferior-most branch, showed species differences in frontal connectivity. In humans, SLF II showed greater connectivity with dorsolateral prefrontal cortex, whereas in chimps SLF II showed greater connectivity with the inferior frontal gyrus. SLF III was right-lateralized and proportionally volumetrically larger in humans, and human SLF III showed relatively reduced connectivity with dorsal premotor cortex and greater extension into the anterior inferior frontal gyrus, especially in the right hemisphere. These results have implications for the evolution of fronto-parietal functions including spatial attention to observed actions, social learning, and tool use, and are in line with previous research suggesting a unique role for the right anterior inferior frontal gyrus in the evolution of human fronto-parietal network architecture.

Regional White Matter Variation Associated with Domain-specific Metacognitive Accuracy

The neural mechanisms that mediate metacognitive ability (the capacity to accurately reflect on one's own cognition and experience) remain poorly understood. An important question is whether metacognitive capacity is a domain-general skill supported by a core neuroanatomical substrate or whether regionally specific neural structures underlie accurate reflection in different cognitive domains. Providing preliminary support for the latter possibility, recent findings have shown that individual differences in metacognitive ability in the domains of memory and perception are related to variation in distinct gray matter volume and resting-state functional connectivity. The current investigation sought to build on these findings by evaluating how metacognitive ability in these domains is related to variation in white matter microstructure. We quantified metacognitive ability across memory and perception domains and used diffusion spectrum imaging to examine the relation between high-resolution measurements of white matter microstructure and individual differences in metacognitive accuracy in each domain. We found that metacognitive accuracy for perceptual decisions and memory were uncorrelated across individuals and that metacognitive accuracy in each domain was related to variation in white matter microstructure in distinct brain areas. Metacognitive accuracy for perceptual decisions was associated with increased diffusion anisotropy in white matter underlying the ACC, whereas metacognitive accuracy for memory retrieval was associated with increased diffusion anisotropy in the white matter extending into the inferior parietal lobule. Together, these results extend previous findings linking metacognitive ability in the domains of perception and memory to variation in distinct brain structures and connections.

Microstructural white matter tissue characteristics are modulated by homocysteine: a diffusion tensor imaging study

Homocysteine level can lead to adverse effects on the brain white matter through endothelial dysfunction, microstructural inflammation, and neurotoxin effects. Despite previously observed associations between elevated homocysteine and macroscopic structural brain changes, it is still unknown whether microstructural associations of homocysteine on brain tissue properties can be observed in healthy subjects with routine MRI. To this end, we investigated potential relationships between homocysteine levels and microstructural measures computed with diffusion tensor imaging (DTI) in a cohort of 338 healthy participants. Significant positive correlations were observed between homocysteine levels and diffusivity measures in the bilateral temporal WM, the brainstem, and the bilateral cerebellar peduncle. This is the first study demonstrating that DTI is sufficiently sensitive to relate microstructural WM properties to homocysteine levels in healthy subjects.

Atlasing the frontal lobe connections and their variability due to age and education: a spherical deconvolution tractography study

In neuroscience, there is a growing consensus that higher cognitive functions may be supported by distributed networks involving different cerebral regions, rather than by single brain areas. Communication within these networks is mediated by white matter tracts and is particularly prominent in the frontal lobes for the control and integration of information. However, the detailed mapping of frontal connections remains incomplete, albeit crucial to an increased understanding of these cognitive functions. Based on 47 high-resolution diffusion-weighted imaging datasets (age range 22-71 years), we built a statistical normative atlas of the frontal lobe connections in stereotaxic space, using state-of-the-art spherical deconvolution tractography. We dissected 55 tracts including U-shaped fibers. We further characterized these tracts by measuring their correlation with age and education level. We reported age-related differences in the microstructural organization of several, specific frontal fiber tracts, but found no correlation with education level. Future voxel-based analyses, such as voxel-based morphometry or tract-based spatial statistics studies, may benefit from our atlas by identifying the tracts and networks involved in frontal functions. Our atlas will also build the capacity of clinicians to further understand the mechanisms involved in brain recovery and plasticity, as well as assist clinicians in the diagnosis of disconnection or abnormality within specific tracts of individual patients with various brain diseases.

Statistical Instability of TBSS Analysis Based on DTI Fitting Algorithm

Voxel-based DTI analysis is an important approach in the comparison of subject groups by detecting and localizing gray and white matter changes in the brain. One of the principal problems for intersubject comparison is the absence of a "gold standard" processing pipeline. As a result, contradictory results may be obtained from identical data using different data processing pipelines, for example, in the data normalization or smoothing procedures. Tract-based spatial statistics (TBSS) shows potential to overcome this problem by automatic detection of white matter changes and decreasing variation in the performed analysis. However, skeleton projection approaches, such as TBSS, critically depend on the accuracy of the diffusion scalar metric estimations. In this work, we demonstrate that the agreement and reliability of TBSS results depend on the applied DTI data processing algorithm. Statistical tests have been performed using two in vivo measured datasets and compared with different implementations of the least squares algorithm. As a result, we recommend repeating TBSS analysis using different fitting algorithms, in particular, using on iteratively-assessed robust estimators, as accurate and more reliable approach in voxel-based analysis, particularly, for TBSS. Repeating TBSS analysis allows one to detect and localize suspicious regions in white matter which were estimated as the regions with significant difference. Finally, we did not find a favorite fitting algorithm (or class of them) which can be marked as more reliable for group comparison.

Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI

Preterm birth is a major public health concern, with the severity and occurrence of adverse outcome increasing with earlier delivery. Being born preterm disrupts a time of rapid brain development: in addition to volumetric growth, the cortex folds, myelination is occurring and there are changes on the cellular level. These neurological events have been imaged non-invasively using diffusion-weighted (DW) MRI. In this population, there has been a focus on examining diffusion in the white matter, but the grey matter is also critically important for neurological health. We acquired multi-shell high-resolution diffusion data on 12 infants born at ≤ 28 weeks of gestational age at two time-points: once when stable after birth, and again at term-equivalent age. We used the Neurite Orientation Dispersion and Density Imaging model (NODDI) (Zhang et al., 2012) to analyse the changes in the cerebral cortex and the thalamus, both grey matter regions. We showed region-dependent changes in NODDI parameters over the preterm period, highlighting underlying changes specific to the microstructure. This work is the first time that NODDI parameters have been evaluated in both the cortical and the thalamic grey matter as a function of age in preterm infants, offering a unique insight into neuro-development in this at-risk population.

White matter integrity and its association with affective and interpersonal symptoms in borderline personality disorder

BACKGROUND

Borderline personality disorder (BPD) is a severe psychiatric disorder involving a range of symptoms including marked affective instability and disturbances in interpersonal interactions. Neuroimaging studies are beginning to provide evidence of altered processing in fronto-limbic network deficits in the disorder, however, few studies directly examine structural connections within this circuitry together with their relation to proposed causative processes and clinical features.

METHODS

In the current study, we investigated whether individuals with BPD (n = 20) have deficits in white matter integrity compared to a matched group of healthy controls (n = 18) using diffusion tensor MRI (DTI). We hypothesized that the BPD group would have decreased fractional anisotropy (FA), a measure of white matter integrity, compared to the controls in white matter tracts connecting frontal and limbic regions, primarily the cingulum, fornix and uncinate fasciculus. We also investigated the extent to which any such deficits related to childhood adversity, as measured by the childhood trauma questionnaire, and symptom severity as measured by the Zanarini rating scale for BPD.

RESULTS

We report decreased white matter integrity in BPD versus controls in the cingulum and fornix. There were no significant relationships between FA and measures of childhood trauma. There were, however, significant associations between FA in the cingulum and clinical symptoms of anger, and in the fornix with affective instability, and measures of avoidance of abandonment from the Zanarini rating scale.

CONCLUSIONS

We report deficits within fronto-limbic connections in individuals with BPD. Abnormalities within the fornix and cingulum were related to severity of symptoms and highlight the importance of these tracts in the pathogenesis of the disorder.

Microstructural brain abnormalities in Huntington's disease: A two-year follow-up

OBJECTIVES

To investigate both cross-sectional and time-related changes of striatal and whole-brain microstructural properties in different stages of Huntington's disease (HD) using diffusion tensor imaging.

EXPERIMENTAL DESIGN

From the TRACK-HD study, premanifest gene carriers (preHD), early manifest HD and controls were scanned at baseline and 2-year follow-up. Stratification of the preHD group into a far (preHD-A) and near (preHD-B) to predicted disease onset was performed. Age-corrected histograms of whole-brain white matter (WM), gray matter (GM) and striatal diffusion measures were computed and normalised by the number of voxels in each subject's data set.

PRINCIPLE OBSERVATIONS

Higher cross-sectional mean, axial and radial diffusivities were found in both WM (P ≤ 0.001) and GM (P ≤ 0.001) of the manifest HD compared to the preHD and control groups. In preHD, only WM axial diffusivity (AD) was higher than in controls (P ≤ 0.01). This finding remained valid only in preHD-B (P ≤ 0.001). AD was also higher in the striatum of preHD-B compared to controls and preHD-A (P ≤ 0.01). Fractional anisotropy (FA) lacked sensitivity in differentiating between the groups. Histogram peak heights were generally lower in manifest HD compared to the preHD and control groups. No longitudinal differences were found in the degree of diffusivity change between the groups in the two year follow-up. There was a significant relationship between diffusivity and neurocognitive measures.

CONCLUSIONS

Alterations in cross-sectional diffusion profiles between manifest HD subjects and controls were evident, both in whole-brain and striatum. In the preHD stage, only AD alterations were found, a finding suggesting that this metric is a sensitive marker for early change in HD prior to disease manifestation. The individual diffusivities were superior to FA in revealing pathologic microstructural brain alterations. Diffusion measures were well related to clinical functioning and disease stage.

White matter disruption at the prodromal stage of Alzheimer's disease: relationships with hippocampal atrophy and episodic memory performance

White matter tract alterations have been consistently described in Alzheimer's disease (AD). In particular, limbic fronto-temporal connections, which are critical to episodic memory function, may degenerate early in the course of the disease. However the relation between white matter tract degeneration, hippocampal atrophy and episodic memory impairment at the earliest stages of AD is still unclear. In this magnetic resonance imaging study, white matter integrity and hippocampal volumes were evaluated in patients with amnestic mild cognitive impairment due to AD (Albert et al., 2011) (n = 22) and healthy controls (n = 15). Performance in various episodic memory tasks was also evaluated in each participant. Relative to controls, patients showed a significant reduction of white matter fractional anisotropy (FA) and increase of radial diffusivity (RD) in the bilateral uncinate fasciculus, parahippocampal cingulum and fornix. Within the patient group, significant intra-hemispheric correlations were notably found between hippocampal grey matter volume and FA in the uncinate fasciculus, suggesting a relationship between atrophy and disconnection of the hippocampus. Moreover, episodic recognition scores were related with uncinate fasciculus FA across patients. These results indicate that fronto-hippocampal connectivity is reduced from the earliest pre-demential stages of AD. Disruption of fronto-hippocampal connections may occur progressively, in parallel with hippocampal atrophy, and may specifically contribute to early initial impairment in episodic memory.

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Limbic fronto-temporal connections (cingulum, uncinate fasciculus and fornix) are altered from the prodromal stage of AD.

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In prodromal AD patients, intra-hemispheric correlations were found between uncinate fasciculus FA and hippocampal atrophy.

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In prodromal AD patients, uncinate fasciculus FA was correlated with scores on episodic recognition.

White matter neuroanatomical differences in young children who stutter

The ability to express thoughts through fluent speech production is a most human faculty, one that is often taken for granted. Stuttering, which disrupts the smooth flow of speech, affects 5% of preschool-age children and 1% of the general population, and can lead to significant communication difficulties and negative psychosocial consequences throughout one's lifetime. Despite the fact that symptom onset typically occurs during early childhood, few studies have yet examined the possible neural bases of developmental stuttering during childhood. Here we present a diffusion tensor imaging study that examined white matter measures reflecting neuroanatomical connectivity (fractional anisotropy) in 77 children [40 controls (20 females), 37 who stutter (16 females)] between 3 and 10 years of age. We asked whether previously reported anomalous white matter measures in adults and older children who stutter that were found primarily in major left hemisphere tracts (e.g. superior longitudinal fasciculus) are also present in younger children who stutter. All children exhibited normal speech, language, and cognitive development as assessed through a battery of assessments. The two groups were matched in chronological age and socioeconomic status. Voxel-wise whole brain comparisons using tract-based spatial statistics and region of interest analyses of fractional anisotropy were conducted to examine white matter changes associated with stuttering status, age, sex, and stuttering severity. Children who stutter exhibited significantly reduced fractional anisotropy relative to controls in white matter tracts that interconnect auditory and motor structures, corpus callosum, and in tracts interconnecting cortical and subcortical areas. In contrast to control subjects, fractional anisotropy changes with age were either stagnant or showed dissociated development among major perisylvian brain areas in children who stutter. These results provide first glimpses into the neuroanatomical bases of early childhood stuttering, and possible white matter developmental changes that may lead to recovery versus persistent stuttering. The white matter changes point to possible structural connectivity deficits in children who stutter, in interrelated neural circuits that enable skilled movement control through efficient sensorimotor integration and timing of movements.

Detection of the arcuate fasciculus in congenital amusia depends on the tractography algorithm

The advent of diffusion magnetic resonance imaging (MRI) allows researchers to virtually dissect white matter fiber pathways in the brain in vivo. This, for example, allows us to characterize and quantify how fiber tracts differ across populations in health and disease, and change as a function of training. Based on diffusion MRI, prior literature reports the absence of the arcuate fasciculus (AF) in some control individuals and as well in those with congenital amusia. The complete absence of such a major anatomical tract is surprising given the subtle impairments that characterize amusia. Thus, we hypothesize that failure to detect the AF in this population may relate to the tracking algorithm used, and is not necessarily reflective of their phenotype. Diffusion data in control and amusic individuals were analyzed using three different tracking algorithms: deterministic and probabilistic, the latter either modeling two or one fiber populations. Across the three algorithms, we replicate prior findings of a left greater than right AF volume, but do not find group differences or an interaction. We detect the AF in all individuals using the probabilistic 2-fiber model, however, tracking failed in some control and amusic individuals when deterministic tractography was applied. These findings show that the ability to detect the AF in our sample is dependent on the type of tractography algorithm. This raises the question of whether failure to detect the AF in prior studies may be unrelated to the underlying anatomy or phenotype.

Constrained spherical deconvolution-based tractography and tract-based spatial statistics show abnormal microstructural organization in Asperger syndrome

BACKGROUND

The aim of this study was to investigate potential differences in neural structure in individuals with Asperger syndrome (AS), high-functioning individuals with autism spectrum disorder (ASD). The main symptoms of AS are severe impairments in social interactions and restricted or repetitive patterns of behaviors, interests or activities.

METHODS

Diffusion weighted magnetic resonance imaging data were acquired for 14 adult males with AS and 19 age, sex and IQ-matched controls. Voxelwise group differences in fractional anisotropy (FA) were studied with tract-based spatial statistics (TBSS). Based on the results of TBSS, a tract-level comparison was performed with constrained spherical deconvolution (CSD)-based tractography, which is able to detect complex (for example, crossing) fiber configurations. In addition, to investigate the relationship between the microstructural changes and the severity of symptoms, we looked for correlations between FA and the Autism Spectrum Quotient (AQ), Empathy Quotient and Systemizing Quotient.

RESULTS

TBSS revealed widely distributed local increases in FA bilaterally in individuals with AS, most prominent in the temporal part of the superior longitudinal fasciculus, corticospinal tract, splenium of corpus callosum, anterior thalamic radiation, inferior fronto-occipital fasciculus (IFO), posterior thalamic radiation, uncinate fasciculus and inferior longitudinal fasciculus (ILF). CSD-based tractography also showed increases in the FA in multiple tracts. However, only the difference in the left ILF was significant after a Bonferroni correction. These results were not explained by the complexity of microstructural organization, measured using the planar diffusion coefficient. In addition, we found a correlation between AQ and FA in the right IFO in the whole group.

CONCLUSIONS

Our results suggest that there are local and tract-level abnormalities in white matter (WM) microstructure in our homogenous and carefully characterized group of adults with AS, most prominent in the left ILF.

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

High-resolution diffusion kurtosis imaging at 3T enabled by advanced post-processing

Diffusion Kurtosis Imaging (DKI) is more sensitive to microstructural differences and can be related to more specific micro-scale metrics (e.g., intra-axonal volume fraction) than diffusion tensor imaging (DTI), offering exceptional potential for clinical diagnosis and research into the white and gray matter. Currently DKI is acquired only at low spatial resolution (2–3 mm isotropic), because of the lower signal-to-noise ratio (SNR) and higher artifact level associated with the technically more demanding DKI. Higher spatial resolution of about 1 mm is required for the characterization of fine white matter pathways or cortical microstructure. We used restricted-field-of-view (rFoV) imaging in combination with advanced post-processing methods to enable unprecedented high-quality, high-resolution DKI (1.2 mm isotropic) on a clinical 3T scanner. Post-processing was advanced by developing a novel method for Retrospective Eddy current and Motion ArtifacT Correction in High-resolution, multi-shell diffusion data (REMATCH). Furthermore, we applied a powerful edge preserving denoising method, denoted as multi-shell orientation-position-adaptive smoothing (msPOAS). We demonstrated the feasibility of high-quality, high-resolution DKI and its potential for delineating highly myelinated fiber pathways in the motor cortex. REMATCH performs robustly even at the low SNR level of high-resolution DKI, where standard EC and motion correction failed (i.e., produced incorrectly aligned images) and thus biased the diffusion model fit. We showed that the combination of REMATCH and msPOAS increased the contrast between gray and white matter in mean kurtosis (MK) maps by about 35% and at the same time preserves the original distribution of MK values, whereas standard Gaussian smoothing strongly biases the distribution.

Normalisation of brain connectivity through compensatory behaviour, despite congenital hand absence

Previously we showed, using task-evoked fMRI, that compensatory intact hand usage after amputation facilitates remapping of limb representations in the cortical territory of the missing hand (Makin et al., 2013a). Here we show that compensatory arm usage in individuals born without a hand (one-handers) reflects functional connectivity of spontaneous brain activity in the cortical hand region. Compared with two-handed controls, one-handers showed reduced symmetry of hand region inter-hemispheric resting-state functional connectivity and corticospinal white matter microstructure. Nevertheless, those one-handers who more frequently use their residual (handless) arm for typically bimanual daily tasks also showed more symmetrical functional connectivity of the hand region, demonstrating that adaptive behaviour drives long-range brain organisation. We therefore suggest that compensatory arm usage maintains symmetrical sensorimotor functional connectivity in one-handers. Since variability in spontaneous functional connectivity in our study reflects ecological behaviour, we propose that inter-hemispheric symmetry, typically observed in resting sensorimotor networks, depends on coordinated motor behaviour in daily life.

DOI:http://dx.doi.org/10.7554/eLife.04605.001

Diffusion tensor imaging and white matter abnormalities in patients with disorders of consciousness

Progress in neuroimaging has yielded new powerful tools which, potentially, can be applied to clinical populations, improve the diagnosis of neurological disorders and predict outcome. At present, the diagnosis of consciousness disorders is limited to subjective assessment and objective measurements of behavior, with an emerging role for neuroimaging techniques. In this review we focus on white matter alterations measured using Diffusion Tensor Imaging on patients with consciousness disorders, examining the most common diffusion imaging acquisition protocols and considering the main issues related to diffusion imaging analyses. We conclude by considering some of the remaining challenges to overcome, the existing knowledge gaps and the potential role of neuroimaging in understanding the pathogenesis and clinical features of disorders of consciousness.

Attentional Profiles and White Matter Correlates in Attention-Deficit/Hyperactivity Disorder Predominantly Inattentive Type

Attention-deficit/hyperactivity disorder (ADHD) is a widely studied neurodevelopmental disorder. It is a highly heterogeneous condition, encompassing different types of expression. The predominantly inattentive type is the most prevalent and the most stable over the lifetime, yet it is the least-studied presentation. To increase understanding of its cognitive profile, 29 children with attention-deficit/hyperactivity disorder of predominantly inattentive type (ADHD-I) and 29 matched controls, aged 7-15 years, had their attentional abilities assessed through the Conners' continuous performance test. Diffusion tensor imaging data were collected for all of the participants using a 3.0-T MRI system. Fractional anisotropy (FA) values were obtained for 20 fiber tracts, and brain-behavior correlations were calculated for 42 of the children. The ADHD-I children differed significantly from the typically developing (TD) children with respect to attentional measures, such as the ability to maintain response-time consistency throughout the task (Hit RT SE and Variability), vigilance (Hit RT ISI and Hit RT ISI SE), processing speed (Hit RT), selective attention (Omissions), sustained attention (Hit RT Block Change), error profile (Response Style), and inhibitory control (Perseverations). Evidence of significant differences between the ADHD-I and the TD participants was not found with respect to the mean FA values in the fiber tracts analyzed. Moderate and strong correlations between performance on the attention indicators and the tract-average FA values were found for the ADHD-I group. Our results contribute to a better characterization of the attentional profile of ADHD-I individuals and suggest that in children and adolescents with ADHD-I, attentional performance is mainly associated with the white matter structure of the long associative fibers that connect anterior-posterior brain areas.

COMMIT: Convex optimization modeling for microstructure informed tractography

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

Effects of age on white matter integrity and negative symptoms in schizophrenia

The current study examined the relationship between white matter integrity as indexed by diffusion tensor imaging and negative symptom severity in schizophrenia. The current study included statistical controls for age effects on the relationship of interest, a major weakness of the existing literature on the subject. Participants included 59 chronic schizophrenia patients, and 31 first-episode schizophrenia patients. Diffusion-weighted neuroimaging was used to calculate fractional anisotropy (FA) in each major brain region (frontal, temporal, parietal, and occipital lobes). Negative symptoms were measured using the Scale for the Assessment of Negative Symptoms (SANS) in all schizophrenia patients. Significant bivariate correlations were observed between global SANS scores and global FA, as well as in most brain regions. These relationships appeared to be driven by SANS items measuring facial expressiveness, poor eye contact, affective flattening, inappropriate affect, poverty of speech, poverty of speech content, alogia, and avolition. However, upon addition of age as a covariate, the observed relationships became non-significant. Further analysis revealed very strong age effects on both FA and SANS scores in the current sample. The findings of this study refute previous reports of significant relationships between DTI variables and negative symptoms in schizophrenia, and they suggest an important confounding variable to be considered in future studies in this population.

Limbic white matter microstructure plasticity reflects recovery from depression

BACKGROUND

White matter microstructure alterations of limbic and reward pathways have been reported repeatedly for depressive episodes in major depressive disorder (MDD) and bipolar disorder (BD). However, findings during remission are equivocal. It was the aim of this study to investigate if white matter microstructure changes during the time course of clinical remission.

METHODS

Fifteen depressed patients (11 MDD, 4 BD) underwent diffusion-weighted MRI both during depression, and during remission following successful antidepressive treatment (average time interval between scans = 6 months). Fractional anisotropy (FA) was sampled along reconstructions of the supero-lateral medial forebrain bundle (slMFB), the cingulum bundle (CB), the uncinate fasciculus (UF), the parahippocampal cingulum (PHC) and the fornix. Repeated measures ANCOVAs controlling for the effect of age were calculated for each tract.

RESULTS

There was a significant main effect of time (inter-scan interval) for mean-FA for the right CB and for the left PHC. For both pathways there was a significant time × age interaction. In the right CB, FA increased in younger patients, while FA decreased in older patients. In the left PHC, a reverse pattern was seen. FA changes in the right CB correlated positively with symptom reductions. Mean-FA of UF, slMFB and fornix did not change between the two time points.

LIMITATIONS

All patients were medicated, sample size, and lack of control group.

CONCLUSIONS

Right CB and left PHC undergo age-dependent plastic changes during the course of remission and may serve as a state marker in depression. UF, slMFB and FO microstructure remains stable.

Does diffusion MRI tell us anything about the white matter? An overview of methods and pitfalls

One key pitfall in diffusion magnetic resonance imaging (dMRI) clinical neuroimaging research is the challenge of understanding and interpreting the results of a complex analysis pipeline. The sophisticated algorithms employed by the analysis software, combined with the relatively non-specific nature of many diffusion measurements, lead to challenges in interpretation of the results. This paper is aimed at an intended audience of clinical researchers who are learning about dMRI or trying to interpret dMRI results, and who may be wondering "Does dMRI tell us anything about the white matter?" We present a critical review of dMRI methods and measures used in clinical neuroimaging research, focusing on the most commonly used analysis methods and the most commonly reported measures. We describe important pitfalls in every section, and provide extensive references for the reader interested in more detail.

Effective electric fields along realistic DTI-based neural trajectories for modelling the stimulation mechanisms of TMS

In transcranial magnetic stimulation (TMS), an applied alternating magnetic field induces an electric field in the brain that can interact with the neural system. It is generally assumed that this induced electric field is the crucial effect exciting a certain region of the brain. More specifically, it is the component of this field parallel to the neuron's local orientation, the so-called effective electric field, that can initiate neuronal stimulation. Deeper insights on the stimulation mechanisms can be acquired through extensive TMS modelling. Most models study simple representations of neurons with assumed geometries, whereas we embed realistic neural trajectories computed using tractography based on diffusion tensor images. This way of modelling ensures a more accurate spatial distribution of the effective electric field that is in addition patient and case specific. The case study of this paper focuses on the single pulse stimulation of the left primary motor cortex with a standard figure-of-eight coil. Including realistic neural geometry in the model demonstrates the strong and localized variations of the effective electric field between the tracts themselves and along them due to the interplay of factors such as the tract's position and orientation in relation to the TMS coil, the neural trajectory and its course along the white and grey matter interface. Furthermore, the influence of changes in the coil orientation is studied. Investigating the impact of tissue anisotropy confirms that its contribution is not negligible. Moreover, assuming isotropic tissues lead to errors of the same size as rotating or tilting the coil with 10 degrees. In contrast, the model proves to be less sensitive towards the not well-known tissue conductivity values.

Validation of network communicability metrics for the analysis of brain structural networks

Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Anatomical and functional plasticity in early blind individuals and the mixture of experts architecture

As described elsewhere in this special issue, recent advances in neuroimaging over the last decade have led to a rapid expansion in our knowledge of anatomical and functional correlations within the normal and abnormal human brain. Here, we review how early blindness has been used as a model system for examining the role of visual experience in the development of anatomical connections and functional responses. We discuss how lack of power in group comparisons may provide a potential explanation for why extensive anatomical changes in cortico-cortical connectivity are not observed. Finally we suggest a framework-cortical specialization via hierarchical mixtures of experts-which offers some promise in reconciling a wide range of functional and anatomical data.

Local termination pattern analysis: a tool for comparing white matter morphology

Disconnections between structures in the brain have long been hypothesized to be the mechanism behind numerous disease states and pathological behavioral phenotypes. Advances in diffusion weighted imaging (DWI) provide an opportunity to study white matter, and therefore brain connectivity, in great detail. DWI-based research assesses white matter at two different scales: voxelwise indexes of anisotropy such as fractional anisotropy (FA) are used to compare small units of tissue and network-based methods compare tractography-based models of whole-brain connectivity. We propose a method called local termination pattern analysis (LTPA) that considers information about both local and global brain connectivity simultaneously. LTPA itemizes the subset of streamlines that pass through a small set of white matter voxels. The "local termination pattern" is a vector defined by counts of these streamlines terminating in pairs of cortical regions. To assess the reliability of our method we applied LTPA exhaustively over white matter voxels to produce complete maps of local termination pattern similarity, based on diffusion spectrum imaging (DSI) data from 11 individuals in triplicate. Here we show that local termination patterns from an individual are highly reproducible across the entire brain. We discuss how LTPA can be deployed into a clinical database and used to characterize white matter morphology differences due to disease, developmental or genetic factors.

Obesity Associated Cerebral Gray and White Matter Alterations Are Interrelated in the Female Brain

Obesity is known to affect the brain's gray matter (GM) and white matter (WM) structure but the interrelationship of such changes remains unclear. Here we used T1-weighted magnetic resonance imaging (MRI) in combination with voxel-based morphometry (VBM) and diffusion-tensor imaging (DTI) with tract-based spatial statistics (TBSS) to assess the relationship between obesity-associated alterations of gray matter density (GMD) and anisotropic water diffusion in WM, respectively. In a small cohort of lean to obese women, we confirmed previous reports of obesity-associated alterations of GMD in brain regions involved in executive control (i.e., dorsolateral prefrontal cortex, DLPFC) and habit learning (i.e., dorsal striatum). Gray matter density alterations of the DLPFC were negatively correlated with radial diffusivity in the entire corpus callosum. Within the genu of the corpus callosum we found a positive correlation with axial diffusivity. In posterior region and inferior areas of the body of the corpus callosum, axial diffusivity correlated negatively with altered GMD in the dorsal striatum. These findings suggest that, in women, obesity-related alterations of GMD in brain regions involved in executive control and habit learning might relate to alterations of associated WM fiber bundles within the corpus callosum.

Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences

Diffusion-weighted imaging (DWI) is known to be prone to artifacts related to motion originating from subject movement, cardiac pulsation, and breathing, but also to mechanical issues such as table vibrations. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involves simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. The scientific community offers strong theoretical and experimental work on noise reduction and orientation distribution function (ODF) reconstruction techniques for HARDI data, where post-acquisition motion correction is widely performed, e.g., using the open-source DTIprep software (1), FSL (the FMRIB Software Library) (2), or TORTOISE (3). Nonetheless, effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk of introducing confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well-controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on a study of the impact of motion correction using four metrics that quantify (1) similarity of fiber orientation distribution functions (fODFs), (2) deviation of local fiber orientations, (3) global brain connectivity via graph diffusion distance (GDD), and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.

Smoking and the developing brain: altered white matter microstructure in attention-deficit/hyperactivity disorder and healthy controls

Brain white matter (WM) tracts, playing a vital role in the communication between brain regions, undergo important maturational changes during adolescence and young adulthood, a critical period for the development of nicotine dependence. Attention-deficit/hyperactivity disorder (ADHD) is associated with increased smoking and widespread WM abnormalities, suggesting that the developing ADHD brain might be especially vulnerable to effects of smoking. This study aims to investigate the effect of smoking on (WM) microstructure in adolescents and young adults with and without ADHD. Diffusion tensor imaging was performed in an extensively phenotyped sample of nonsmokers (n = 95, 50.5% ADHD), irregular smokers (n = 41, 58.5% ADHD), and regular smokers (n = 50, 82.5% ADHD), aged 14-24 years. A whole-brain voxelwise approach investigated associations of smoking, ADHD and their interaction, with WM microstructure as measured by fractional anisotropy (FA) and mean diffusivity (MD). Widespread alterations in FA and MD were found for regular smokers compared to irregular and nonsmokers, mainly located in the corpus callosum and WM tracts surrounding the basal ganglia. Several regions overlapped with regions of altered FA for ADHD versus controls, albeit in different directions. Irregular and nonsmokers did not differ, and ADHD and smoking did not interact. Results implicate that smoking and ADHD have independent effects on WM microstructure, and possibly do not share underlying mechanisms. Two mechanisms may play a role in the current results. First, smoking may cause alterations in WM microstructure in the maturing brain. Second, pre-existing WM microstructure differences possibly reflect a risk factor for development of a smoking addiction.

Application of advanced neuroimaging modalities in pediatric traumatic brain injury

Neuroimaging is commonly used for the assessment of children with traumatic brain injury and has greatly advanced how children are acutely evaluated. More recently, emphasis has focused on how advanced magnetic resonance imaging methods can detect subtler injuries that could relate to the structural underpinnings of the neuropsychological and behavioral alterations that frequently occur. We examine several methods used for the assessment of pediatric brain injury. Susceptibility-weighted imaging is a sensitive 3-dimensional high-resolution technique in detecting hemorrhagic lesions associated with diffuse axonal injury. Magnetic resonance spectroscopy acquires metabolite information, which serves as a proxy for neuronal (and glial, lipid, etc) structural integrity and provides sensitive assessment of neurochemical alterations. Diffusion-weighted imaging is useful for the early detection of ischemic and shearing injury. Diffusion tensor imaging allows better structural evaluation of white matter tracts. These methods are more sensitive than conventional imaging in demonstrating subtle injury that underlies a child's clinical symptoms. There also is an increasing desire to develop computational methods to fuse imaging data to provide a more integrated analysis of the extent to which components of the neurovascular unit are affected. The future of traumatic brain injury neuroimaging research is promising and will lead to novel approaches to predict and improve outcomes.

Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding

Diffusion tensor imaging (DTI) offers rich insights into the physical characteristics of white matter (WM) fiber tracts and their development in the brain, facilitating a network representation of brain's traffic pathways. Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging. The high dimensionality of these connectivity networks necessitates the development of methods that identify the connectivity building blocks or sub-network components that characterize the underlying variation in the population. In addition, the projection of the subject networks into the basis set provides a low dimensional representation of it, that teases apart different sources of variation in the sample, facilitating variation-specific statistical analysis. We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive basis set, as well as, additional basis sets representing variational sources in the population like age and pathology. The proposed framework is applied to a study of diffusion-based connectivity in subjects with autism that shows localized sparse sub-networks which mostly capture the changes related to pathology and developmental variations.

Widespread effects of alcohol on white matter microstructure

BACKGROUND

Evidence suggests that chronic misuse of alcohol may preferentially affect the integrity of frontal white matter (WM) tracts, which can impact executive functions important to achieve and maintain abstinence.

METHODS

Global and regional WM microstructure was assessed using diffusion magnetic resonance measures of fractional anisotropy (FA) for 31 abstinent alcoholics (ALC) with an average of 25 years of abuse and approximately 5 years of sobriety and 20 nonalcoholic control (NC) participants. Data processing was conducted with FreeSurfer and FSL processing streams. Voxelwise processing of the FA data was carried out using tract-based spatial statistics. Clusters of significance were created to provide a quantitative summary of highly significant regions within the voxelwise analysis.

RESULTS

Widespread, bilateral reductions in FA were observed in ALC as compared to NC participants in multiple frontal, temporal, parietal, and cerebellar WM tracts. FA in the left inferior frontal gyrus was associated with drinking severity.

CONCLUSIONS

This study found widespread reductions in WM integrity in a group of ALC compared to NC participants, with most pronounced effects in frontal and superior tracts. Decreased FA throughout the frontostriatal circuits that mediate inhibitory control may result in impulsive behavior and inability to maintain sobriety.

Microstructural brain abnormalities and symptom dimensions in child and adolescent patients with obsessive-compulsive disorder: a diffusion tensor imaging study

BACKGROUND

The aims of this study were to determine white matter (WM) microstructure abnormalities in obsessive-compulsive disorder (OCD) using diffusion tensor imaging, and to investigate whether these abnormalities differ according to OCD symptom dimensions.

METHODS

Sixty-three child and adolescent OCD patients (11-18 years old) and 37 healthy subjects matched for gender, age, and estimated intelligence quotient were assessed by means of psychopathology scales and diffusion tensor magnetic resonance imaging.

RESULTS

Compared with healthy controls OCD patients showed a significant decrease (t = 3.79, P = .049 FDR-corrected) in fractional anisotropy (FA) in the anterior region of the corpus callosum (CC). In addition, mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) values were significantly increased in OCD compared with controls in the CC and in several WM regions of the cingulate, frontal and occipital lobes, basal ganglia, cerebellum, and pons. Compared with healthy controls, OCD patients presenting the harm/checking dimension showed decreased FA in the CC and in the left anterior cingulate gyrus and caudate nucleus, whereas patients with a predominant contamination/washing symptom dimension presented significantly decreased FA in the left midbrain, lentiform nucleus, insula, and thalamus, and increased MD, AD, and RD in both the anterior lobes of cerebellum and in the pons.

CONCLUSIONS

The findings suggest WM abnormalities at the microstructural level in the pathogenesis of OCD. Moreover, WM abnormalities in OCD may vary according to the specific OCD symptom dimensions, thus indicating the clinical heterogeneity of the condition.

Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis

Objective

Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas.

Methods

Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients.

Results

Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance.

Conclusions

Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.

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Subnetwork of hyperconnectivity in juvenile myoclonic epilepsy

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Hyperconnectivity in primary motor, parietal and subcortical regions

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Network-based statistics is a valuable tool for predicting functional cognitive deficits.

Structural and functional correlates of behavioral pattern separation in the hippocampus and medial temporal lobe

Structures of the medial temporal lobe (MTL) are known to be involved in declarative memory processes. However, little is known about how age-related changes in MTL structures, white matter integrity, and functional connectivity affect pattern separation processes in the MTL. In this study, we used magnetic resonance imaging (MRI) to measure the volumes of MTL regions of interest, including hippocampal subfields (dentate gyrus, CA3, CA1, and subiculum) in healthy older and younger adults. Additionally, we used diffusion tensor imaging to measure white matter integrity for both groups. Finally, we used functional MRI to acquire resting functional connectivity measures for both groups. We show that, along with age, the volume of left CA3/dentate gyrus predicts memory performance. Differences in fractional anisotropy and the strength of resting functional connections between the hippocampus and other cortical structures implicated in memory processing were not significant predictors of performance. As previous studies have only hinted, it seems that the size of left CA3/dentate gyrus contributes more to successful discrimination between similar mnemonic representations than other hippocampal sub-fields, MTL structures, and other neuroimaging correlates. Accordingly, the implications of aging and atrophy on lure discrimination capacities are discussed.

Age related differences in reaction time components and diffusion properties of normal-appearing white matter in healthy adults

Deterioration of the white matter (WM) is viewed as the neural substrate of age differences in speed of information processing (reaction time, RT). However, the relationship between WM and RT components is rarely examined in healthy aging. We assessed the relationship between RT components derived from the Ratcliff diffusion model and micro-structural properties of normal-appearing WM (NAWM) in 90 healthy adults (age 18-82 years). We replicated all major extant findings pertaining to age differences in RT components and WM: lower drift rate, greater response conservativeness, longer non-decision time, lower fractional anisotropy (FA), greater mean (MD), axial (AD) and radial (RD) diffusivity were associated with advanced age. Age differences in anterior regions of the cerebral WM exceeded those in posterior regions. However, the only relationship between RT components and WM was the positive association between DR in the body of the corpus callosum and non-decision time. Thus, in healthy adults, age differences in NAWM diffusion properties are not a major contributor to age differences in RT components. Longitudinal studies with more precise and specific estimates of regional myelin content and evaluation of the contribution of age-related vascular risk factors are necessary to understand cerebral substrates of age-related cognitive slowing.

Short association fibres of the insula-temporoparietal junction in early psychosis: a diffusion tensor imaging study

Evidence shows that there are reductions in gray matter volume (GMV) and changes in long association white matter fibres within the left insula-temporoparietal junction (TPJ) during the early stages of psychotic disorders but less is known about short association fibres (sAFs). In this study we sought to characterise the changes in sAFs and associated volumetric changes of the left insula-TPJ during the early stages of psychosis. Magnetic resonance imaging was obtained from a sample of young people with psychosis (n = 42) and healthy controls (n = 45), and cortical parcellations of the left insula-TPJ were used as seeding masks to reconstruct 13 sAFs. Compared to healthy counterparts, the psychosis group showed significant reductions in fractional anisotropy (FA) in the sAFs connecting the superior (STG) and middle temporal gyri (MTG) and as well as reduced GMV within the inferior temporal gyrus and increased white matter volume (WMV) within Heschl's gyrus (HG). Furthermore, adolescent-onset psychosis subjects (onset 18 year or earlier) showed FA reductions in the STG-HG sAF when compared to adult-onset subjects, but this was not associated with changes in GMV nor WMV of the STG or HG. These findings suggest that during the early stages of psychosis, changes in sAFs and associated cortical GMV and WMV appear to occur independently, however age of onset of a psychotic syndrome/disorder influences the pattern of neuroanatomical abnormalities.

Global tractography with embedded anatomical priors for quantitative connectivity analysis

Tractography algorithms provide us with the ability to non-invasively reconstruct fiber pathways in the white matter (WM) by exploiting the directional information described with diffusion magnetic resonance. These methods could be divided into two major classes, local and global. Local methods reconstruct each fiber tract iteratively by considering only directional information at the voxel level and its neighborhood. Global methods, on the other hand, reconstruct all the fiber tracts of the whole brain simultaneously by solving a global energy minimization problem. The latter have shown improvements compared to previous techniques but these algorithms still suffer from an important shortcoming that is crucial in the context of brain connectivity analyses. As no anatomical priors are usually considered during the reconstruction process, the recovered fiber tracts are not guaranteed to connect cortical regions and, as a matter of fact, most of them stop prematurely in the WM; this violates important properties of neural connections, which are known to originate in the gray matter (GM) and develop in the WM. Hence, this shortcoming poses serious limitations for the use of these techniques for the assessment of the structural connectivity between brain regions and, de facto, it can potentially bias any subsequent analysis. Moreover, the estimated tracts are not quantitative, every fiber contributes with the same weight toward the predicted diffusion signal. In this work, we propose a novel approach for global tractography that is specifically designed for connectivity analysis applications which: (i) explicitly enforces anatomical priors of the tracts in the optimization and (ii) considers the effective contribution of each of them, i.e., volume, to the acquired diffusion magnetic resonance imaging (MRI) image. We evaluated our approach on both a realistic diffusion MRI phantom and in vivo data, and also compared its performance to existing tractography algorithms.

White matter abnormalities associated with military PTSD in the context of blast TBI

Mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD) are common among recent military veterans and involve substantial symptom overlap, making clinical distinction and effective intervention difficult. Emerging evidence of cerebral white matter abnormalities associated with mTBI may provide a biological measure to inform diagnosis and treatment, but the potentially confounding effects between PTSD and mTBI have largely gone unexamined. We collected diffusion imaging data from 133 recently-deployed American service members who developed PTSD and/or sustained mTBI, or had neither condition. Effects of PTSD and mTBI on traditional tensor-based measures of cerebral white matter integrity (fractional anisotropy [FA] and mean diffusivity [MD]) were compared in anatomical regions of interest and individual voxels throughout the brain. Generalized FA (GFA), which allows for multiple fiber orientations per voxel, was also included to improve sensitivity in white matter areas containing crossing or diverging axon bundles. PTSD was consistently associated with high GFA in select brain regions, greater likelihood of regions and voxels with abnormally low MD, and a greater number of voxels with abnormally high FA, while mTBI was associated with fewer high MD regions. Overall, PTSD was associated with more restricted diffusion (low MD) and greater anisotropy (high GFA) in regions of crossing/diverging fibers poorly characterized by a single tensor (FA), suggesting that interstitial fibers may be involved. Contrary to earlier results in a sample without PTSD, mTBI was not associated with anisotropy abnormalities, perhaps indicating the cooccurrence of PTSD and mTBI requires special consideration with regard to structural brain connectivity.

Altered white matter microstructure is associated with social cognition and psychotic symptoms in 22q11.2 microdeletion syndrome

22q11.2 Microdeletion Syndrome (22q11DS) is a highly penetrant genetic mutation associated with a significantly increased risk for psychosis. Aberrant neurodevelopment may lead to inappropriate neural circuit formation and cerebral dysconnectivity in 22q11DS, which may contribute to symptom development. Here we examined: (1) differences between 22q11DS participants and typically developing controls in diffusion tensor imaging (DTI) measures within white matter tracts; (2) whether there is an altered age-related trajectory of white matter pathways in 22q11DS; and (3) relationships between DTI measures, social cognition task performance, and positive symptoms of psychosis in 22q11DS and typically developing controls. Sixty-four direction diffusion weighted imaging data were acquired on 65 participants (36 22q11DS, 29 controls). We examined differences between 22q11DS vs. controls in measures of fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD), using both a voxel-based and region of interest approach. Social cognition domains assessed were: Theory of Mind and emotion recognition. Positive symptoms were assessed using the Structured Interview for Prodromal Syndromes. Compared to typically developing controls, 22q11DS participants showed significantly lower AD and RD in multiple white matter tracts, with effects of greatest magnitude for AD in the superior longitudinal fasciculus. Additionally, 22q11DS participants failed to show typical age-associated changes in FA and RD in the left inferior longitudinal fasciculus. Higher AD in the left inferior fronto-occipital fasciculus (IFO) and left uncinate fasciculus was associated with better social cognition in 22q11DS and controls. In contrast, greater severity of positive symptoms was associated with lower AD in bilateral regions of the IFO in 22q11DS. White matter microstructure in tracts relevant to social cognition is disrupted in 22q11DS, and may contribute to psychosis risk.

Interindividual variation in fornix microstructure and macrostructure is related to visual discrimination accuracy for scenes but not faces

Transection of the nonhuman primate fornix has been shown to impair learning of configurations of spatial features and object-in-scene memory. Although damage to the human fornix also results in memory impairment, it is not known whether there is a preferential involvement of this white-matter tract in spatial learning, as implied by animal studies. Diffusion-weighted MR images were obtained from healthy participants who had completed versions of a task in which they made rapid same/different discriminations to two categories of highly visually similar stimuli: (1) virtual reality scene pairs; and (2) face pairs. Diffusion-MRI measures of white-matter microstructure [fractional anisotropy (FA) and mean diffusivity (MD)] and macrostructure (tissue volume fraction, f) were then extracted from the fornix of each participant, which had been reconstructed using a deterministic tractography protocol. Fornix MD and f measures correlated with scene, but not face, discrimination accuracy in both discrimination tasks. A complementary voxelwise analysis using tract-based spatial statistics suggested the crus of the fornix as a focus for this relationship. These findings extend previous reports of spatial learning impairments after fornix transection in nonhuman primates, critically highlighting the fornix as a source of interindividual variation in scene discrimination in humans.

Altered fronto-striatal fiber topography and connectivity in obsessive-compulsive disorder

Fronto-striatal circuits are hypothesized to be involved in the pathophysiology of obsessive-compulsive disorder (OCD). Within this circuitry, ventral frontal regions project fibers to the ventral striatum (VS) and dorsal frontal regions to the dorsal striatum. Resting state fMRI research has shown higher functional connectivity between the orbitofrontal cortex (OFC) and the dorsal part of the VS in OCD patients compared to healthy controls (HC). Therefore, we hypothesized that in OCD the OFC predominantly project fibers to the more dorsal part of the VS, and that the structural connectivity between the OFC and VS is higher compared to HC. A total of 20 non-medicated OCD patients and 20 HC underwent diffusion-weighted imaging. Connectivity-based parcellation analyses were performed with the striatum as seed region and the OFC, dorsolateral prefrontal cortex, and dorsal anterior cingulate cortex as target regions. Obtained connectivity maps for each frontal region of interest (ROI) were normalized into standard space, and Z-component (dorsal–ventral) coordinate of center-of-gravity (COG) were compared between two groups. Probabilistic tractography was performed to investigate diffusion indices of fibers between the striatum and frontal ROIs. COG Z-component coordinates of connectivity maps for OFC ROI were located in the more dorsal part of the VS in OCD patients compared to HC. Fractional anisotropy of fibers between the OFC and the striatum was higher in OCD patients compared to HC. Part of the pathophysiology of OCD might be understood by altered topography and structural connectivity of fibers between the OFC and the striatum.

Disruption of brain white matter microstructure in women with anorexia nervosa

BACKGROUND

The etiology of anorexia nervosa is still unknown. Multiple and distributed brain regions have been implicated in its pathophysiology, implying a dysfunction of connected neural circuits. Despite these findings, the role of white matter in anorexia nervosa has been rarely assessed. In this study, we used diffusion tensor imaging (DTI) to characterize alterations of white matter microstructure in a clinically homogeneous sample of patients with anorexia nervosa.

METHODS

Women with anorexia nervosa (restricting subtype) and healthy controls underwent brain DTI. We used tract-based spatial statistics to compare fractional anisotropy (FA) and mean diffusivity (MD) maps between the groups. Furthermore, axial (AD) and radial diffusivity (RD) measures were extracted from regions showing group differences in either FA or MD.

RESULTS

We enrolled 19 women with anorexia nervosa and 19 healthy controls in our study. Patients with anorexia nervosa showed significant FA decreases in the parietal part of the left superior longitudinal fasciculus (SLF; p(FWE) < 0.05), with increased MD and RD but no differences in AD. Patients with anorexia nervosa also showed significantly increased MD in the fornix (p(FWE) < 0.05), accompanied by decreased FA and increased RD and AD.

LIMITATIONS

Limitations include our modest sample size and cross-sectional design.

CONCLUSION

Our findings support the presence of white matter pathology in patients with anorexia nervosa. Alterations in the SLF and fornix might be relevant to key symptoms of anorexia nervosa, such as body image distortion or impairments in body-energy-balance and reward processes. The differences found in both areas replicate those found in previous DTI studies and support a role for white matter pathology of specific neural circuits in individuals with anorexia nervosa.

A diffusion tensor imaging family study of the fornix in schizophrenia

Diffusion tensor imaging (DTI) studies suggest abnormalities in the white matter microstructure of the fornix in schizophrenia patients. Research evaluating schizophrenia patient and relatives also suggests that the white matter microstructure of the fornix is heritable. However, previous studies have been hindered by limited DTI methodology. Therefore, the goal of this study was to assess whether fornix abnormalities were related to the genetic liability for schizophrenia using the novel methodological approach of assessing multiple metrics of along-tract measurements, in addition to whole-tract means. Twenty-five schizophrenia patients, 24 adult non-psychotic first-degree biological relatives, and 27 community controls underwent neuroimaging. No group differences were found for any of the DTI metrics using the classical whole-tract measures of the fornix. Along-tract analysis detected local increases in fractional anisotropy (FA) in the right fimbria of the fornix for relatives compared to patients and controls corrected for false discovery rate. No significant associations were found between symptoms, global functioning, or IQ and whole-tract FA means in schizophrenia patients or relatives. Increased FA in non-psychotic relatives could represent a compensatory mechanism to guard against psychosis or an abnormality associated with the genetic liability for the disorder. These findings underscore the importance of obtaining along-tract measurements, in addition to whole-tract measurements to fully understand white matter abnormalities in schizophrenia.

Degree of corticospinal tract damage correlates with motor function after stroke

OBJECTIVES

Direct injury to the corticospinal tract (CST) is a major factor defining motor impairment after stroke. Diffusion tensor imaging (DTI) tractography allows definition of the CST. We sought to determine whether DTI-based assessment of the degree of CST damage correlates with motor impairment at each phase of ischemic stroke.

METHODS

We evaluated patients at the acute (3-7 days), subacute (30 days), and chronic (90 days) phases of ischemic stroke with DTI and clinical motor scores (upper extremity Fugl-Myer test [UE-FM], motor items of the National Institutes of Health Stroke Scale [mNIHSS]). The CST was identified and virtual fiber numbers (FN) were calculated for the affected and contralateral CST. We used Spearman correlation to study the relationship of FN ratio (FNr) (affected/unaffected CST) with motor scores at each time point, and the regression model to study the association of the acute parameters with chronic motor scores.

RESULTS

We studied 23 patients. Mean age was 66.7 (±12) years. FNr correlated with UE-FM score in the acute (r = 0.50, P = 0.032), subacute (r = 0.57, P = 0.007), and chronic (r = 0.67, P = 0.0008) phase, and with mNIHSS in the acute (r = -0.48, P = 0.043), subacute (r = -0.58, P = 0.006), and chronic (r = -0.75, P = 0.0001) phase. The combination of acute NIHSS and FNr significantly predicted chronic UE-FM score (r = 0.74, P = 0.0001).

INTERPRETATION

DTI-defined degree of CST injury correlates with motor impairment at each phase of ischemic stroke. The combination of baseline FNr and NIHSS predicts motor outcome. DTI-derived CST assessment could become a surrogate marker of motor impairment in the design of neurorestorative clinical trials.

Head rotational acceleration characteristics influence behavioral and diffusion tensor imaging outcomes following concussion

A majority of traumatic brain injuries (TBI) in motor vehicle crashes and sporting environments are mild and caused by high-rate acceleration of the head. For injuries caused by rotational acceleration, both magnitude and duration of the acceleration pulse were shown to influence injury outcomes. This study incorporated a unique rodent model of rotational acceleration-induced mild TBI (mTBI) to quantify independent effects of magnitude and duration on behavioral and neuroimaging outcomes. Ninety-two Sprague-Dawley rats were exposed to head rotational acceleration at peak magnitudes of 214 or 350 krad/s(2) and acceleration pulse durations of 1.6 or 3.4 ms in a full factorial design. Rats underwent a series of behavioral tests including the Composite Neuroscore (CN), Elevated Plus Maze (EPM), and Morris Water Maze (MWM). Ex vivo diffusion tensor imaging (DTI) of the fixed brains was conducted to assess the effects of rotational injury on brain microstructure as revealed by the parameter fractional anisotropy (FA). While the injury did not cause significant locomotor or cognitive deficits measured with the CN and MWM, respectively, a main effect of duration was consistently observed for the EPM. Increased duration caused significantly greater activity and exploratory behaviors measured as open arm time and number of arm changes. DTI demonstrated significant effects of both magnitude and duration, with the FA of the amygdala related to both the magnitude and duration. Increased duration also caused FA changes at the interface of gray and white matter. Collectively, the findings demonstrate that the consequences of rotational acceleration mTBI were more closely associated with duration of the rotational acceleration impulse, which is often neglected as an independent factor, and highlight the need for animal models of TBI with strong biomechanical foundations to associate behavioral outcomes with brain microstructure.

Deep white matter in Huntington's disease

White matter (WM) abnormalities have already been shown in presymptomatic (Pre-HD) and symptomatic HD subjects using Magnetic Resonance Imaging (MRI). In the present study, we examined the microstructure of the long-range large deep WM tracts by applying two different MRI approaches: Diffusion Tensor Imaging (DTI) -based tractography, and T2*weighted (iron sensitive) imaging. We collected Pre-HD subjects (n = 25), HD patients (n = 25) and healthy control subjects (n = 50). Results revealed increased axial (AD) and radial diffusivity (RD) and iron levels in Pre-HD subjects compared to controls. Fractional anisotropy decreased between the Pre-HD and HD phase and AD/RD increased and although impairment was pervasive in HD, degeneration occurred in a pattern in Pre-HD. Furthermore, iron levels dropped for HD patients. As increased iron levels are associated with remyelination, the data suggests that Pre-HD subjects attempt to repair damaged deep WM years before symptoms occur but this process fails with disease progression.

Multimodal magnetic resonance imaging study of treatment-naïve adults with attention-deficit/hyperactivity disorder

Background

Attention-Deficit/Hiperactivity Disorder (ADHD) is a prevalent disorder, but its neuroanatomical circuitry is still relatively understudied, especially in the adult population. The few morphometric magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) studies available to date have found heterogeneous results. This may be at least partly attributable to some well-known technical limitations of the conventional voxel-based methods usually employed to analyze such neuroimaging data. Moreover, there is a great paucity of imaging studies of adult ADHD to date that have excluded patients with history of use of stimulant medication.

Methods

A newly validated method named optimally-discriminative voxel-based analysis (ODVBA) was applied to multimodal (structural and DTI) MRI data acquired from 22 treatment-naïve ADHD adults and 19 age- and gender-matched healthy controls (HC).

Results

Regarding DTI data, we found higher fractional anisotropy in ADHD relative to HC encompassing the white matter (WM) of the bilateral superior frontal gyrus, right middle frontal left gyrus, left postcentral gyrus, bilateral cingulate gyrus, bilateral middle temporal gyrus and right superior temporal gyrus; reductions in trace (a measure of diffusivity) in ADHD relative to HC were also found in fronto-striatal-parieto-occipital circuits, including the right superior frontal gyrus and bilateral middle frontal gyrus, right precentral gyrus, left middle occipital gyrus and bilateral cingulate gyrus, as well as the left body and right splenium of the corpus callosum, right superior corona radiata, and right superior longitudinal and fronto-occipital fasciculi. Volumetric abnormalities in ADHD subjects were found only at a trend level of significance, including reduced gray matter (GM) in the right angular gyrus, and increased GM in the right supplementary motor area and superior frontal gyrus.

Conclusions

Our results suggest that adult ADHD is associated with neuroanatomical abnormalities mainly affecting the WM microstructure in fronto-parieto-temporal circuits that have been implicated in cognitive, emotional and visuomotor processes.